Riemannian ANOVA Statistics
Permutation Statistic for a Super Sample
Compute Pillai's Trace Statistic
Compute the Log Wilks' Lambda Statistic
Normalize Rows of a Matrix
Harmonize Vector Images Using ComBat
Format a Matrix as a Packed dpoMatrix
Frechet ANOVA Test Statistic
Compute p-values using permutation test
Harmonize Tangent Images Across Batches Using Rigid Correction
Compute OAS-Shrunk Correlation Matrix from Time Series
Provides statistical methods for analyzing samples of symmetric positive definite (SPD) matrices, particularly functional connectivity matrices from neuroimaging data. Implements Fréchet ANOVA (Dubey and Müller (2019) <doi:10.1093/biomet/asz052>) for testing differences between groups in metric spaces, and Riemannian ANOVA methods that leverage tangent space geometry with classic multivariate test statistics including Wilks' Lambda and Pillai's trace. Also includes harmonization techniques for removing batch effects in multi-site studies: ComBat-based harmonization (Honnorat et al. (2024) <doi:10.1016/j.media.2023.103043>) and rigid harmonization (Simeon et al. (2022) <doi:10.3389/fninf.2022.769274>). Builds on 'riemtan' package infrastructure for efficient computation with multiple Riemannian metrics.